Problem statement

With the rise of MonkeyPox cases in Europe, in preparation of an appropriate response, our team has been tasked with developing an update for the leadership of our state health department regarding the state of MPX. We are specifically interested in understanding how case rates may differ by region and various demographic factors. The demographic factor we are particularly interested in is gender.

Methods

Data sources

We used four data sets to tackle this project: Data on monkeypox cases in the EU/EEA, European population denominators, European census statistics data and world country regions data. Data on monkeypox cases in the EU/EEA was accessed from the European Center for Disease Prevention and Control (ECDC). The European population denominator data source is from the European commission, the EU census statistics data source is from European census statistics 2011.

Data cleaning

From data on monkeypox cases in the EU/EEA, we selected three variables named: Country code, date cases were reported of which we generated months on which monkeypox cases were reported and the number of monkeypox cases reported.We then selected only two variables from population denominator data set being country code which was renamed from geo and time period, then we filtered the data set by time period of year 2022 in order for us to have the most recent time period.

Further more we selected two variables from census data: country code and sex because we were interested at the distribution of monkeypox rate by gender. Additionally , we selected two variables from world country region data set being country code and sub regions which were only for Europe by filtering only country code that matches the one that are available in monkeypox cases data set.

All the data sets were merged using country code to allow us generate new variables according to the objective of the project: we created monkeypox rate per region per month and monkeypox rate per sex for all countries in the Europe which reported monkey pox cases.The missing records and records that were not applicable for our project were removed from the data set.

Analytic Methods

A table and a plot containing bar chart and a line chart were created from our data set after joining monkeypox cases data set, population denominator and world country region data set. The bar chart represents the monkeypox rate in each european region categorised by different month when reported in year 2022, while the line chart represents the monkeypox rate for different month in each region. Then the scatter plot was created to measure the linear relationship between monkeypox rate and sex.

Results

Table 1 shows Monkeypox rates by regions from May to August in 2022.

Figure1

Figure 1 shows a visualization of monkeypox case rates by month for different regions within the EU. There has been an increase in monkeypox case rates in all EU regions since May 2022, which then began to subside in August.

Figure2

Figure 2 shows the relationship of monkeypox rate and month for different region of Europe.There has been an increase in monkeypox case rates in all EU regions since May 2022, which then began to subside in August.

Figure3

Figure 3 shows the scatter plot of between monkeypox rates and female population, indicating the absence of linear relationship between our variables.

Figure4

Figure 4 shows the scatter plot of between monkeypox rates and male population, indicating the absence of linear relationship between our variables.

Discussion

The results of our analysis suggest that there is no correlation between gender and monkeypox case rates, as can be seen in figure 3 and 4. From figure the monkeypox rates were less compared to other months, in July all the regions experience a huge increase of monkeypox rate of which Western Europe region had the highest rate compared to other regions. Figure 2 depicts that though case rates are increasing in all EU regions, there has been a drastic decrease in case rates during August especially for Southern Europe followed by Western Europe. In the Eastern and Northern Europe, they are not subsiding as quickly as in the other two regions. Based on our investigation, we suggest an increase in surveillance in Eastern and Northern Europe as they need more support in dealing with an outbreak in monkeypox cases.